Big Data e-Infrastructure for Educational Data
Big Data e-Infrastructure for Educational Data will realize a Big Data e-infrastructure to accompany the scientific activities of SLATE by developing a big data e-infrastructure. The e-infrastructure will host the raw educational data and will support access, assessment, analysis, comparison and manipulation of the data. Machine-to-machine interfaces will enable communication with external data sources, such as data from the University of Bergen and MOOC-systems nationally and internationally.
On the systems level, the data will be realized by means of a data-lake, storing raw educational data and other education related information. The system will provide carefully designed Machine Learning algorithms to support scientific and service tasks.
Tools will be developed in close collaboration with the researchers of SLATE. Further tools are provided for other stakeholders in the Educational sector, such as public authorities, teachers and learners, which receive services based on state-of-the-art scientific insights.
Project website: Big Data e-Infrastructure for Educational Data